Using AI for Abnormal Behavior Detection

This is a presentation I used during my talk at the IT Summit Turkey 2019.

Transcript

1. Daron Yöndem
   http://daron.me
   @daronyondem
   

   View Slide

2. • Out of the Box Anomaly Detection for Cloud Apps
   • Anomaly Detection in the world of IoT
   • Anomaly Detector for Everyone
   

   View Slide

3. • Risky IP address
   • Login failures
   • Admin activity
   • Inactive accounts
   • Location
   • Impossible travel
   • Device and user agent
   • Activity rate
   

   View Slide

4. • Entity behavioral analytics (UEBA)
   • Machine learning (ML)
   

   View Slide

5. View Slide

6. View Slide

7. • Azure IoT Edge, Azure Stream Analytics offers built-in machine
   learning based anomaly detection
   • AnomalyDetection_SpikeAndDip and
   AnomalyDetection_ChangePoint
   

   View Slide

8. An AI service that helps you
   foresee problems before
   they occur
   

   View Slide

9. View Slide

10. View Slide

11. View Slide

12. View Slide

13. View Slide

14. Microsoft Cloud App Security Product Page
    https://drn.fyi/375O6ML
    Anomaly Detection with Azure Stream Analytics and ML
    https://drn.fyi/33ZlpPu
    Online Playground for Anomaly Detector
    https://drn.fyi/2Qhqz5C
    Azure Anomaly Detector Video
    https://drn.fyi/2CHyl0z
    

    View Slide

15. http://daron.me | @daronyondem
    Download slides here;
    http://decks.daron.me
    

    View Slide